Download [COURSERA] BAYESIAN METHODS FOR MACHINE LEARNING [FCO] Torrent

Torrent Contents Size: 2.2 GB

[COURSERA] BAYESIAN METHODS FOR MACHINE LEARNING [FCO]

▼ show more 118 files

001. Think bayesian & Statistics review.mp4	MP4	23.7 MB
001. Think bayesian & Statistics review.srt	SRT	10.6 KB
002. Bayesian approach to statistics.mp4	MP4	17.1 MB
002. Bayesian approach to statistics.srt	SRT	6.9 KB
003. How to define a model.mp4	MP4	10 MB
003. How to define a model.srt	SRT	4.1 KB
004. Example thief & alarm.mp4	MP4	59.8 MB
004. Example thief & alarm.srt	SRT	12.5 KB
005. Linear regression.mp4	MP4	50.1 MB
005. Linear regression.srt	SRT	11.2 KB
006. Analytical inference.mp4	MP4	13.8 MB
006. Analytical inference.srt	SRT	4.9 KB
007. Conjugate distributions.mp4	MP4	9.2 MB
007. Conjugate distributions.srt	SRT	3.4 KB
008. Example Normal, precision.mp4	MP4	16.4 MB
008. Example Normal, precision.srt	SRT	6.7 KB
009. Example Bernoulli.mp4	MP4	14 MB
009. Example Bernoulli.srt	SRT	5.4 KB
010. Latent Variable Models.mp4	MP4	36.8 MB
010. Latent Variable Models.srt	SRT	15.1 KB
011. Probabilistic clustering.mp4	MP4	21.7 MB
011. Probabilistic clustering.srt	SRT	8 KB
012. Gaussian Mixture Model.mp4	MP4	29.2 MB
012. Gaussian Mixture Model.srt	SRT	12.9 KB
013. Training GMM.mp4	MP4	31.6 MB
013. Training GMM.srt	SRT	13.7 KB
014. Example of GMM training.mp4	MP4	31.3 MB
014. Example of GMM training.srt	SRT	13.1 KB
015. Jensen's inequality & Kullback Leibler divergence.mp4	MP4	28.4 MB
015. Jensen's inequality & Kullback Leibler divergence.srt	SRT	11.9 KB
016. Expectation-Maximization algorithm.mp4	MP4	32 MB
016. Expectation-Maximization algorithm.srt	SRT	13.4 KB
017. E-step details.mp4	MP4	66.2 MB
017. E-step details.srt	SRT	13 KB
018. M-step details.mp4	MP4	19.2 MB
018. M-step details.srt	SRT	8 KB
019. Example EM for discrete mixture, E-step.mp4	MP4	56.4 MB
019. Example EM for discrete mixture, E-step.srt	SRT	10.1 KB
020. Example EM for discrete mixture, M-step.mp4	MP4	65.5 MB
020. Example EM for discrete mixture, M-step.srt	SRT	12.4 KB
021. Summary of Expectation Maximization.mp4	MP4	20.3 MB
021. Summary of Expectation Maximization.srt	SRT	8.1 KB
022. General EM for GMM.mp4	MP4	62.5 MB
022. General EM for GMM.srt	SRT	14.2 KB
023. K-means from probabilistic perspective.mp4	MP4	28.5 MB
023. K-means from probabilistic perspective.srt	SRT	11.2 KB
024. K-means, M-step.mp4	MP4	31 MB
024. K-means, M-step.srt	SRT	7.2 KB
025. Probabilistic PCA.mp4	MP4	39 MB
025. Probabilistic PCA.srt	SRT	16 KB
026. EM for Probabilistic PCA.mp4	MP4	21.8 MB
026. EM for Probabilistic PCA.srt	SRT	8.7 KB
027. Why approximate inference.mp4	MP4	15.7 MB
027. Why approximate inference.srt	SRT	6.3 KB
028. Mean field approximation.mp4	MP4	77.3 MB
028. Mean field approximation.srt	SRT	11.7 KB
029. Example Ising model.mp4	MP4	68.2 MB
029. Example Ising model.srt	SRT	16.9 KB
030. Variational EM & Review.mp4	MP4	17.4 MB
030. Variational EM & Review.srt	SRT	7.6 KB
031. Topic modeling.mp4	MP4	16.8 MB
031. Topic modeling.srt	SRT	6.6 KB
032. Dirichlet distribution.mp4	MP4	20.5 MB
032. Dirichlet distribution.srt	SRT	8.2 KB
033. Latent Dirichlet Allocation.mp4	MP4	18.2 MB
033. Latent Dirichlet Allocation.srt	SRT	6.6 KB
034. LDA E-step, theta.mp4	MP4	75.6 MB
034. LDA E-step, theta.srt	SRT	9.4 KB
035. LDA E-step, z.mp4	MP4	59.2 MB
035. LDA E-step, z.srt	SRT	7.5 KB
036. LDA M-step & prediction.mp4	MP4	93.5 MB
036. LDA M-step & prediction.srt	SRT	11.6 KB
037. Extensions of LDA.mp4	MP4	15.8 MB
037. Extensions of LDA.srt	SRT	6.2 KB
038. Monte Carlo estimation.mp4	MP4	44.5 MB
038. Monte Carlo estimation.srt	SRT	16.9 KB
039. Sampling from 1-d distributions.mp4	MP4	47 MB
039. Sampling from 1-d distributions.srt	SRT	16.5 KB
040. Markov Chains.mp4	MP4	47.1 MB
040. Markov Chains.srt	SRT	15.7 KB
041. Gibbs sampling.mp4	MP4	61.4 MB
041. Gibbs sampling.srt	SRT	12.9 KB
042. Example of Gibbs sampling.mp4	MP4	27.6 MB
042. Example of Gibbs sampling.srt	SRT	9.3 KB
043. Metropolis-Hastings.mp4	MP4	29.9 MB
043. Metropolis-Hastings.srt	SRT	9.7 KB
044. Metropolis-Hastings choosing the critic.mp4	MP4	42 MB
044. Metropolis-Hastings choosing the critic.srt	SRT	9.2 KB
045. Example of Metropolis-Hastings.mp4	MP4	36.6 MB
045. Example of Metropolis-Hastings.srt	SRT	12.5 KB
046. Markov Chain Monte Carlo summary.mp4	MP4	26.8 MB
046. Markov Chain Monte Carlo summary.srt	SRT	12.4 KB
047. MCMC for LDA.mp4	MP4	46.7 MB
047. MCMC for LDA.srt	SRT	20.8 KB
048. Bayesian Neural Networks.mp4	MP4	34 MB
048. Bayesian Neural Networks.srt	SRT	14.8 KB
049. Scaling Variational Inference & Unbiased estimates.mp4	MP4	19.5 MB
049. Scaling Variational Inference & Unbiased estimates.srt	SRT	8.3 KB
050. Modeling a distribution of images.mp4	MP4	32.2 MB
050. Modeling a distribution of images.srt	SRT	14.2 KB
051. Using CNNs with a mixture of Gaussians.mp4	MP4	24.9 MB
051. Using CNNs with a mixture of Gaussians.srt	SRT	9.7 KB
052. Scaling variational EM.mp4	MP4	47.8 MB
052. Scaling variational EM.srt	SRT	18.9 KB
053. Gradient of decoder.mp4	MP4	19.3 MB
053. Gradient of decoder.srt	SRT	7.6 KB
054. Log derivative trick.mp4	MP4	20.8 MB
054. Log derivative trick.srt	SRT	8 KB
055. Reparameterization trick.mp4	MP4	25.2 MB
055. Reparameterization trick.srt	SRT	9.4 KB
056. Learning with priors.mp4	MP4	30.4 MB
056. Learning with priors.srt	SRT	8.7 KB
057. Dropout as Bayesian procedure.mp4	MP4	35 MB
057. Dropout as Bayesian procedure.srt	SRT	8.3 KB
058. Sparse variational dropout.mp4	MP4	29.6 MB
058. Sparse variational dropout.srt	SRT	7.5 KB
059. Nonparametric methods.mp4	MP4	18.2 MB
059. Nonparametric methods.srt	SRT	7.5 KB
060. Gaussian processes.mp4	MP4	24.2 MB
060. Gaussian processes.srt	SRT	9.6 KB
061. GP for machine learning.mp4	MP4	16.4 MB
061. GP for machine learning.srt	SRT	6.4 KB
062. Derivation of main formula.mp4	MP4	69.9 MB
062. Derivation of main formula.srt	SRT	9.5 KB
063. Nuances of GP.mp4	MP4	36.8 MB
063. Nuances of GP.srt	SRT	13.8 KB
064. Bayesian optimization.mp4	MP4	31.2 MB
064. Bayesian optimization.srt	SRT	12.5 KB
065. Applications of Bayesian optimization.mp4	MP4	16.6 MB
065. Applications of Bayesian optimization.srt	SRT	6.1 KB
[FTU Forum].url	URL	204.8 B
[FreeCoursesOnline.Me].url	URL	102.4 B
[FreeTutorials.Us].url	URL	102.4 B

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[COURSERA] BAYESIAN METHODS FOR MACHINE LEARNING [FCO]

Torrent Contents Size: 2.2 GB

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